MIS Chapter 6
The four primary sources of low quality data include
1.Customers intentionally enter inaccurate data to protect their privacy 2.Different entry standards and formats 3.Operators enter abbreviated or erroneous data by accident or to save time 4.Third party and external data contains inconsistencies, inaccuracies, and errors
Primary key
A field (or group of fields) that uniquely identifies a given entity in a table
data warehouse
A logical collection of data - gathered from many different operational databases - that supports business analysis activities and decision-making tasks
Entity
A person, place, thing, transaction, or event about which data is stored
Foreign key
A primary key of one table that appears as an attribute in another table and acts to provide a logical relationship between the two tables
Extraction, transformation, and loading (ETL)
A process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse
Proof-of-work
A requirement to define an expensive computer calculation, also called mining, that needs to be performed in order to create a new group of trustless transactions (blocks) on the distributed ledger or blockchain
Blockchain
A type of distributed ledger technology consisting of data structure blocks that may contain data or programs, with each block holding batches of individual transactions and the results of any executables. Each block contains a time stamp and a link to a previous block.
Database management systems
Allows users to create, read, update, and delete data in a relational database
Data mart
Contains a subset of data warehouse data
Access Control
Determines types of user access, such as read-only access
access level
Determines who has access to the different types of information
Transactional Data
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
Analytical data
Encompasses all organizational data, and its primary purpose is to support the performing of managerial analysis tasks
Blockchain
Formed by linking together blocks, data structures containing previous hash and data
Real-time data
Immediate, up-to-date data.
Performance
Measures how quickly a system performs a certain process or transaction
Password
Provides authentication of the user
Real-time system
Provides real-time information in response to requests
Ledger
Records classified and summarized transactional data
Scalability
Refers to how well a system can adapt to increased demands
Data redundancy
The duplication of data or storing the same data in multiple places
Genesis block
The first block created in the blockchain
master data management
The practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including such entities as customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated across organizational systems
The four primary traits of the value of data
Type, Timeliness, Quality, Governance
Record
a collection of related data elements
Hash
a function that converts an input of letters and numbers into an encrypted output of a fixed length
Data cleansing or scrubbing
a process that weeks out and fixes or discards inconsistent incorrect, or incomplete data
Data lake
a storage repository that holds a vast amount of raw data in its original format until the business needs it
Proof-of-stake
a way to validate transactions and achieve a distributed consensus
Characteristics of High-quality data
accuracy, completeness, consistency, uniqueness, timeliness
Data cube
common term for the representation of multidimensional information
data dictionary
compiles all of the metadata about the data elements in the data model
data visualization
describes technologies that allow users to see or visualize data to transform information into a business perspective
Metadata
details about data
Dirty data
erroneous or flawed data
Data validation
includes the tests and evaluations used to determine compliance with data governance polices to ensure correctness of data
Data model
logical data structures that detail the relationships among data elements using graphics or pictures
Database
maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)
Data integrity
measures the quality of data
Data visualization tools
move beyond Excel graphs and charts into sophisticated analysis techniques such as controls, instruments, maps, time-series graphs, and more
Distributed computing
process and manages algorithms across many machines in a computing environment
Data governance
refers to the overall management of the availability, usability, integrity, and security of company data
Integrity constraint
rules that help ensure the quality of information
Data element
smallest basic unit of information
data aggregation
the collection of data from various sources for the purpose of data processing
Attribute
the data elements associated with an entity
Business intelligence dashboards
track corporate metrics such as critical success factors and key performance indicators and include advanced capabilities such as interactive controls, allowing users to manipulate data for analysis